Web publishers often include advertising messages in the web pages that they serve to users. Such advertising messages may either be for the benefit of an advertiser other than the publisher, or may promote products or services sold by the publisher. For example, an online merchant may include on its web pages advertisements promoting products or services sold by the online merchant.
It is typical for each page served by a publisher to have a number of “slots” (also referred to herein as distinguished locations) that each may contain an advertising message. It is frequently true that, for each slot, several different advertising messages are eligible to be included in that slot, such that the publisher may select any of these eligible advertising messages to include in the display. It is common for a publisher to select from among the advertising messages eligible for a particular slot the advertising message expected to have the greatest value to the publisher, such as the advertising message expected to produce the greatest measure of revenue and/or profit for the publisher.
It is common to determine the level of revenue and/or profit each eligible advertising message is expected to produce by dividing the total revenue and/or profit that the advertising message has produced when included in a slot during a foregoing period of time by the number of times the advertising message has been included in the display during that period to obtain a “mean value” or “expected value” for the advertising message in the slot. This approach often provides a useful basis for selecting an eligible advertising message to include in a slot where each eligible message has been included in the display (1) a statistically significant number of times (2) under relevant conditions that are similar to those present at the time the slot is being filled. Where this situation does not exist, however, one or more of the advertising messages may be misvalued based upon a scarcity of representative experience with the advertising message, causing the publisher to select an advertising message other than the optimal advertising message and adversely affect its overall results.
In some cases, to counter this limitation of the expected value approach to selecting a message, publishers have used a modified approach where opportunities to present a message in a particular slot are allocated to one of two modes: a fixed percentage of opportunities are allocated to an “exploitation” mode that uses the expected value approach to selecting a message described above, while the remaining fixed percentage of opportunities are allocated to an “experimentation” mode that seeks to increase the number of times that underexposed advertising messages are included in the display, in order to obtain a more reliable valuation of these messages.